A resilient feedback linearization control scheme for smart grids under cyber-physical disturbances
Bibliographic record
Abstract
A cyber-enabled parametric control scheme is proposed for efficient transient frequency and phase stabilization in the power grid. Different implementations of the proposed control are investigated in this work. First, a centralized control scheme is proposed where the controller relies on timely phasor measurement unit (PMU) information about the grid to employ fast-acting energy storage systems for stabilization. Further, a decentralized controller implementation assumes information about the rest of the grid is not available, and hence acts based on local PMU measurements. For the case of cyber attacks targeting communication channels and resulting in large delays or absence of PMU data, we propose a robust combined control scheme where the controller operates in a centralized mode by default and switches to the decentralized scheme if PMU information is delayed or not available. Numerical results show the effectiveness and robustness of the proposed controller against physical and cyber-physical disturbances in the 39-bus 10-generator New England power system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".